期刊名称：Current Journal of Applied Science and Technology
印刷版ISSN：2457-1024
出版年度：2020
卷号：39
期号：48
页码：96-110
DOI：10.9734/cjast/2020/v39i4831205
语种：English
出版社：Sciencedomain International
摘要：Agriculture is becoming more integrated in the agro-food chain and the global market, while environmental, food safety and quality are also increasingly impacting on the sector. It is facing with new challenges to meet growing demands for food, to be internationally competitive and to produce agricultural products of high quality. To cope with these challenges, Agriculture requires a continuous and sustainable increase in productivity and efficiency on all levels of agricultural production, while resources like water, energy, fertilizers etc. need to be used carefully and efficiently in order to protect and maintain the soil quality and environment. Consequently, Agriculture needs help in handling the complexity, uncertainty and fuzziness inherent in this domain. It requires new solutions for all aspects of agricultural farming, including precision farming and optimized resource application. Artificial Intelligence (AI) technology helps various industries to improve production and productivity. In agriculture, AI also allows farmers to increase their productivity and reduce negative environmental impacts. AI is changing the way our food is processed, where emissions from the agricultural sector have decreased by 20%. Together with precision agriculture (PA) and other emerging technologies, artificial intelligence (AI) can play a key role in modernizing agricultural practices and achieving the goal of improving the productivity of alternative arable cropping systems. In offering progressive change with advanced approaches, AI's future in agriculture is well ahead. The aim of this paper is to review various agricultural intelligence applications and to reduce the use of colossal amounts of chemicals with the aid of these technologies, resulting in reduced spending, improved soil fertility and increased productivity. With AI tools and machine learning, farmers can improve yields, protect their crops and have a much more reliable source of food.
